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ZHOU Hongwei, ZHANG Dongheng, GENG Ruixu, et al. Phased array radar trajectory tracking and vital signs monitoring based on adaptive motion state sensing[J]. Journal of Radars, in press. doi: 10.12000/JR26032
Citation: ZHOU Hongwei, ZHANG Dongheng, GENG Ruixu, et al. Phased array radar trajectory tracking and vital signs monitoring based on adaptive motion state sensing[J]. Journal of Radars, in press. doi: 10.12000/JR26032
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Phased Array Radar Trajectory Tracking and Vital Signs Monitoring Based on Adaptive Motion State Sensing

DOI: 10.12000/JR26032 CSTR: 32380.14.JR26032

  • School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China

Funds:  The National Natural Science Foundation of China (62201542), The Fundamental Research Funds for the Central Universities
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  • Corresponding author: ZHANG Dongheng, dongheng@ustc.edu.cn
  • Received Date: 2026-01-28
    Available Online: 2026-04-25
    Abstract
  • With the rapid aging of the population, the rising demand for home-based care and chronic disease monitoring in older adults has increased interest in radar-based technologies for indoor human trajectory tracking and vital sign detection. Existing studies mainly use multiple-input multiple-output (MIMO) systems, which face limitations such as low signal-to-noise ratio (SNR) and data redundancy. In contrast, phased array radars offer better sensing reliability in complex indoor environments, thanks to higher SNR and lower data volume. However, current indoor sensing systems encounter two main challenges when applying phased array radars. First, traditional beam scheduling strategies often lose targets when tracking close-range, highly maneuverable humans. Second, achieving simultaneous trajectory tracking and real-time vital sign detection remains difficult without adaptive switching mechanisms based on target movement. To address these issues, this paper first compares MIMO and phased array radars, along with the average revisit time of different beam-scheduling strategies for tracking indoor human movements. It also proposes an adaptive real-time monitoring system for human motion states based on phased array radar. This system dynamically switches modes based on human movement: during motion, it employs a strategy combining coarse scanning, adaptive fine scanning, and sum-and-difference beam angle measurement for real-time trajectory tracking; when stationary, it shifts to a vital sign monitoring mode to capture respiration and heartbeat signals. Experimental results show that the proposed system provides stable indoor trajectory tracking and reliable vital sign monitoring, laying the groundwork for home-based smart health monitoring systems.

     

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